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Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African–European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene–environment interaction—defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa—we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Antibiotic overuse has promoted the spread of antimicrobial resistance (AMR) with significant health and economic consequences. Surveillance of resistance reservoirs, like the rarely explored oral microbiome, is necessary to combat AMR. We characterised the development of the paediatric oral resistome and investigated its role in dental caries in 221 twin children sampled over the first decade of life. From 535 oral metagenomes, we identified 309 antimicrobial resistance genes (ARGs), which significantly clustered by age, with the influence of host genetics on antimicrobial resistance increasing over time. Our results suggest the mobilisation potential of ARGs increased with age as Tn916 transposase was co-located with more species and ARGs as children grew. Dental caries compared to health was associated with a depletion of ARGs and species, which was reversed when restored. Our results highlight the dynamic nature of the paediatric oral resistome, and its potential role in transmission of AMR and dysbiosis.

Oral squamous cell carcinoma (OSCC) in the young (50 years), without known carcinogenic risk factors, is on the rise globally. Whole genome duplication (WGD) has been shown to occur at higher rates in cancers without an identifiable carcinogenic agent. We aimed to evaluate the prevalence of WGD in a cohort of OSCC patients under the age of 50 years.Whole genome sequencing (WGS) was performed on 28 OSCC patients from the Sydney Head and Neck Cancer Institute (SHNCI) biobank. An additional nine cases were obtained from The Cancer Genome Atlas (TCGA).WGD was seen in 27 of 37 (73%) cases. Non-synonymous, somatic TP53 mutations occurred in 25 of 27 (93%) cases of WGD and were predicted to precede WGD in 21 (77%). WGD was significantly associated with larger tumor size (p = 0.01) and was frequent in patients with recurrences (87%, p = 0.36). Overall survival was significantly worse in those with WGD (p = 0.05).Our data, based on one of the largest WGS datasets of young patients with OSCC, demonstrates a high frequency of WGD and its association with adverse pathologic characteristics and clinical outcomes. TP53 mutations also preceded WGD, as has been described in other tumors without a clear mutagenic driver.

Prostate cancer is characterised by significant global disparity; mortality rates in Sub-Saharan Africa are double to quadruple those in Eurasia1. Hypothesising unknown interplay between genetic and non-genetic factors, tumour genome profiling envisages contributing mutational processes2,3. Through whole-genome sequencing of treatment-naïve prostate cancer from 183 ethnically/globally distinct patients (African versus European), we generate the largest cancer genomics resource for Sub-Saharan Africa. Identifying ~2 million somatic variants, Africans carried the greatest burden. We describe a new molecular taxonomy using all mutational types and ethno-geographic identifiers, including Asian. Defined as Global Mutational Subtypes (GMS) A–D, although Africans presented within all subtypes, we found GMS-B to be ‘African-specific’ and GMS-D ‘African-predominant’, including Admixed and European Africans. Conversely, Europeans from Australia, Africa and Brazil predominated within ‘mutationally-quiet’ and ethnically/globally ‘universal’ GMS-A, while European Australians shared a higher mutational burden with Africans in GMS-C. GMS predicts clinical outcomes; reconstructing cancer timelines suggests four evolutionary trajectories with different mutation rates (GMS-A, low 0.968/year versus D, highest 1.315/year). Our data suggest both common genetic factors across extant populations and regional environmental factors contributing to carcinogenesis, analogous to gene-environment interaction defined here as a different effect of an environmental surrounding in persons with different ancestries or vice versa. We anticipate GMS acting as a proxy to intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Objective To adapt ‘fishplots’ to describe real-time evolution of SARS-CoV-2 genomic clusters. Results This novel analysis adapted the fishplot to depict the size and duration of circulating genomic clusters over time in New South Wales, Australia. It illuminated the effectiveness of interventions on the emergence, spread and eventual elimination of clusters and distilled genomic data into clear information to inform public health action.

Whooping cough, or pertussis, is a highly transmissible respiratory infection caused by Bordetella pertussis. Due to the high burden of pertussis, vaccine programmes were introduced internationally and in Australia since the 1950s. This has resulted in a significant decrease of pertussis infections. However, since the 1990s the number of pertussis notifications has increased considerably. Currently circulating B. pertussis strains differ in vaccine antigen composition compared to strains that circulated in the pre-vaccination era. These genetic differences are thought to contribute, in part, to the re-emergence of pertussis in Australia and around the world. Whole genome sequencing (WGS) can resolve minute differences in circulating strains and provides unparalleled resolution of vaccine antigens. This high-resolution snapshot can provide clues that enable more targeted public health interventions. However, pertussis is primarily diagnosed with culture-independent diagnostic assays which offer fast turnaround result times and reduced laboratory costs, eliminating the need to culture isolates. Current WGS methods require a cultured isolate, resulting in an absence of B. pertussis genome sequences in the post vaccination era. This scarcity has, in turn, limited understanding of currently circulating strains and respective vaccine antigen compositions.Recent advancements of WGS technologies have allowed direct sequencing of clinical specimens without the need for a cultured isolate. However, recovering reliable sequence data from clinical samples of low bacterial load infections such as B. pertussis is a pressing challenge. We sought to increase the yield of B. pertussis sequences direct from a clinical sample by evaluating widely available WGS library preparation methods.We report that the Illumina DNA prep library preparation kit combined with deep sequencing allowed the detection of important surveillance information such as allelic variations in the B. pertussis vaccine antigens. Further, our method generates high coverage over the 23S ribosomal RNA of B. pertussis enabling macrolide resistance to be easily determined. Overall, this method can improve surveillance of B. pertussis, by monitoring changes in vaccine antigens, detecting antimicrobial resistance and guiding Public Health control interventions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic surveillance has been vital in understanding the spread of coronavirus disease 2019 (COVID-19), the emergence of viral escape mutants, and variants of concern. However, low viral loads in clinical specimens affect variant calling for phylogenetic analyses and detection of low-frequency variants, important in uncovering infection transmission chains. We systematically evaluated three widely adopted SARS-CoV-2 whole-genome sequencing methods for their sensitivity, specificity, and ability to reliably detect low-frequency variants. Our analyses reveal that the ARTIC v3 protocol consistently displays high sensitivity for generating complete genomes at low viral loads compared with the probe-based Illumina Respiratory Viral Oligo panel and a pooled long-amplicon method. We show substantial variability in the number and location of low-frequency variants detected using the three methods, highlighting the importance of selecting appropriate methods to obtain high-quality sequence data from low-viral-load samples for public health and genomic surveillance purposes.

Community transmission of the new coronavirus SARS-CoV-2 is a major public health concern that remains difficult to assess. We present a genomic survey of SARS-CoV-2 from a during the first 10 weeks of COVID-19 activity in New South Wales, Australia. Transmission events were monitored prospectively during the critical period of implementation of national control measures. SARS-CoV-2 genomes were sequenced from 209 patients diagnosed with COVID-19 infection between January and March 2020. Only a quarter of cases appeared to be locally acquired and genomic-based estimates of local transmission rates were concordant with predictions from a computational agent-based model. This convergent assessment indicates that genome sequencing provides key information to inform public health action and has improved our understanding of the COVID-19 evolution from outbreak to epidemic.

In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China1,2. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.

Multidrug- and colistin-resistant Salmonella enterica serotype 4,[5],12:i:- sequence type 34 is present in Europe and Asia. Using genomic surveillance, we determined that this sequence type is also endemic to Australia. Our findings highlight the public health benefits of genome sequencing-guided surveillance for monitoring the spread of multidrug-resistant mobile genes and isolates.

Maintaining optimal infection prevention and control (IPC) in a busy, clinical environment is challenging. Video-reflexive ethnography (VRE) is a collaborative, interventionist approach to practice improvement. We hypothesised that giving clinicians opportunities to view and reflect on video footage of everyday ward activities would raise awareness of, and suggest strategies to reduce, pathogen transmission risks. We undertook a VRE project, between March and September 2013, in two tertiary hospital surgical wards, with persistently high methicillin resistant Staphylococcus aureus (MRSA) endemicity, despite previous IPC interventions.This study was a retrospective/prospective observational study, using interrupted time-series analyses, to assess the effects of the VRE project on hand hygiene compliance, inpatient MRSA infections (newly infected patients, per 1000 occupied bed days) and inpatient MRSA colonisation prevalence, measured by serial point prevalence surveys. Follow-up continued until June 2016.The VRE project was associated with changes in IPC behaviour and outcomes. Hand hygiene compliance increased (from 62% to 75%; p 0.0001) and MRSA colonisation prevalence decreased significantly, in both wards (baseline 42%; average post-VRE 12%; p=0.0001), MRSA infection rate decreased in one ward. Interpretation of results was complicated by a potential confounding effect of unplanned environmental hydrogen peroxide decontamination (HPD). Improved hand hygiene compliance was a predicted outcome of VRE, but also a potential contributor to reduced MRSA transmission.Separate contributions of VRE (the intervention), HPD and hand hygiene compliance were uncertain, but their combined effect was significantly reduced MRSA endemicity, which previously had been resistant to attempted IPC interventions.

Candida glabrata can rapidly acquire mutations that result in drug resistance, especially to azoles and echinocandins. Identification of genetic mutations is essential, as resistance detected in vitro can often be correlated with clinical failure. We examined the feasibility of using whole genome sequencing (WGS) for genome-wide analysis of antifungal drug resistance in C. glabrata. The aim was torecognize enablers and barriers in the implementation WGS and measure its effectiveness. This paper outlines the key quality control checkpoints and essential components of WGS methodology to investigate genetic markers associated with reduced susceptibility to antifungal agents. It also estimates the accuracy of data analysis and turn-around-time of testing. Phenotypic susceptibility of 12 clinical, and one ATCC strain of C. glabrata was determined through antifungal susceptibility testing. These included three isolate pairs, from three patients, that developed rise in drug minimum inhibitory concentrations. In two pairs, the second isolate of each pair developed resistance to echinocandins. The second isolate of the third pair developed resistance to 5-flucytosine. The remaining comprised of susceptible and azole resistant isolates. Single nucleotide polymorphisms (SNPs) in genes linked to echinocandin, azole and 5-flucytosine resistance were confirmed in resistant isolates through WGS using the next generation sequencing. Non-synonymous SNPs in antifungal resistance genes such as FKS1, FKS2, CgPDR1, CgCDR1 and FCY2 were identified. Overall, an average of 98% of the WGS reads of C. glabrata isolates mapped to the reference genome with about 75-fold read depth coverage. The turnaround time and cost were comparable to Sanger sequencing. In conclusion, WGS of C. glabrata was feasible in revealing clinically significant gene mutations involved in resistance to different antifungal drug classes without the need for multiple PCR/DNA sequencing reactions. This represents a positive step towards establishing WGS capability in the clinical laboratory for simultaneous detection of antifungal resistance conferring substitutions.

The objective of this chapter is to demonstrate the use of hybrid modelling for management decision support. The chapter presents three separate case studies that are unified both by the common theme of using different modelling techniques in a hybrid manner and by the health and social care context. The first case study combines the use of system dynamics and agent-based modelling to better understand and control the spread of a specific drug-resistant pathogen in hospitals; the second case study demonstrates how a hybrid system dynamics and discrete-event simulation model can support clinical and management decision making in the context of sexual health services; and the third case study is dedicated to the investigation of a hybrid model that consists of a system-dynamics-inspired cell-based population model and a discrete-event simulation model, and is used to explore the performance of the contact centre for long-term care for people aged 65 and over.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of preventable nosocomial infections and is endemic in hospitals worldwide. The effectiveness of infection control policies varies significantly across hospital settings. The impact of the hospital context towards the rate of nosocomial MRSA infections and the success of infection control is understudied. We conducted a modelling study to evaluate several infection control policies in surgical, intensive care, and medical ward specialties, each with distinct ward conditions and policies, of a tertiary public hospital in Sydney, Australia. We reconfirm hand hygiene as the most successful policy and find it to be necessary for the success of other policies. Active screening for MRSA, patient isolation in single-bed rooms, and additional staffing were found to be less effective. Across these ward specialties, MRSA transmission risk varied by 13% and reductions in the prevalence and nosocomial incidence rate of MRSA due to infection control policies varied by up to 45%. Different levels of infection control were required to reduce and control nosocomial MRSA infections for each ward specialty. Infection control policies and policy targets should be specific for the ward and context of the hospital. The model we developed is generic and can be calibrated to represent different ward settings and pathogens transmitted between patients indirectly through health care workers. This can aid the timely and cost effective design of synergistic and context specific infection control policies.

Background Improved tuberculosis control and the need to contain the spread of drug-resistant strains provide a strong rationale for exploring tuberculosis transmission dynamics at the population level. Whole-genome sequencing provides optimal strain resolution, facilitating detailed mapping of potential transmission pathways. Methods We sequenced 22 isolates from a Mycobacterium tuberculosis cluster in New South Wales, Australia, identified during routine 24-locus mycobacterial interspersed repetitive unit typing. Following high-depth paired-end sequencing using the Illumina HiSeq 2000 platform, two independent pipelines were employed for analysis, both employing read mapping onto reference genomes as well as de novo assembly, to control biases in variant detection. In addition to single-nucleotide polymorphisms, the analyses also sought to identify insertions, deletions and structural variants. Results Isolates were highly similar, with a distance of 13 variants between the most distant members of the cluster. The most sensitive analysis classified the 22 isolates into 18 groups. Four of the isolates did not appear to share a recent common ancestor with the largest clade; another four isolates had an uncertain ancestral relationship with the largest clade. Conclusion Whole genome sequencing, with analysis of single-nucleotide polymorphisms, insertions, deletions, structural variants and subpopulations, enabled the highest possible level of discrimination between cluster members, clarifying likely transmission pathways and exposing the complexity of strain origin. The analysis provides a basis for targeted public health intervention and enhanced classification of future isolates linked to the cluster.

Most problems arising from the operation of the health system are studied and addressed using conventional reductionist methods, which reduce, isolate, and freeze aspects of the system at a given time. This fails to deal with the dynamic complexity inherent in the health system and which is often the source of the problem. The result is that all too often, well intentioned interventions make the original problem worse by failing to fully understand the complexities involved in the origin of a problem (Sterman, 2000). In this article, we introduce system simulation as a means of exposing the underlying causes and systemic structures of problems within the health care system, as well as providing a tool for assessing the likely impact of new interventions. The following sections will examine the advantages of simulation, areas of application, how simulation experiments can overcome some of the limitations of randomised control trials (RCTs), and various simulation methodologies as well as the challenges of conducting simulation experiments.